Barrett, The Honors College at Arizona State University proudly showcases the work of undergraduate honors students by sharing this collection exclusively with the ASU community.

Barrett accepts high performing, academically engaged undergraduate students and works with them in collaboration with all of the other academic units at Arizona State University. All Barrett students complete a thesis or creative project which is an opportunity to explore an intellectual interest and produce an original piece of scholarly research. The thesis or creative project is supervised and defended in front of a faculty committee. Students are able to engage with professors who are nationally recognized in their fields and committed to working with honors students. Completing a Barrett thesis or creative project is an opportunity for undergraduate honors students to contribute to the ASU academic community in a meaningful way.

Displaying 1 - 10 of 44
136728-Thumbnail Image.png
Description
This project was centered around designing a processor model (using the C programming language) based on the Coldfire computer architecture that will run on third party software known as Open Virtual Platforms. The end goal is to have a fully functional processor that can run Coldfire instructions and utilize peripheral

This project was centered around designing a processor model (using the C programming language) based on the Coldfire computer architecture that will run on third party software known as Open Virtual Platforms. The end goal is to have a fully functional processor that can run Coldfire instructions and utilize peripheral devices in the same way as the hardware used in the embedded systems lab at ASU. This project would cut down the substantial amount of time students spend commuting to the lab. Having the processor directly at their disposal would also encourage them to spend more time outside of class learning the hardware and familiarizing themselves with development on an embedded micro-controller. The model will be accurate, fast and reliable. These aspects will be achieved through rigorous unit testing and use of the OVP platform which provides instruction accurate simulations at hundreds of MIPS (million instructions per second) for the specified model. The end product was able to accurately simulate a subset of the Coldfire instructions at very high rates.
ContributorsDunning, David Connor (Author) / Burger, Kevin (Thesis director) / Meuth, Ryan (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2014-12
136364-Thumbnail Image.png
Description
The purpose of this project was to program a Raspberry Pi to be able to play music from both local storage on the Pi and from internet radio stations such as Pandora. The Pi also needs to be able to play various types of file formats, such as mp3 and

The purpose of this project was to program a Raspberry Pi to be able to play music from both local storage on the Pi and from internet radio stations such as Pandora. The Pi also needs to be able to play various types of file formats, such as mp3 and FLAC. Finally, the project is also to be driven by a mobile app running on a smartphone or tablet. To achieve this, a client server design was employed where the Raspberry Pi acts as the server and the mobile app is the client. The server functionality was achieved using a Python script that listens on a socket and calls various executables that handle the different formats of music being played. The client functionality was achieved by programming an Android app in Java that sends encoded commands to the server, which the server decodes and begins playing the music that command dictates. The designs for both the client and server are easily extensible and allow for any future modifications to the project to be easily made.
ContributorsStorto, Michael Olson (Author) / Burger, Kevin (Thesis director) / Meuth, Ryan (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2015-05
Description
As modern advancements in medical technology continue to increase overall life expectancy, hospitals and healthcare systems are finding new and more efficient ways of storing extensive amounts of patient healthcare information. This progression finds people increasingly dependent on hospitals as the primary providers of medical data, ranging from immunization records

As modern advancements in medical technology continue to increase overall life expectancy, hospitals and healthcare systems are finding new and more efficient ways of storing extensive amounts of patient healthcare information. This progression finds people increasingly dependent on hospitals as the primary providers of medical data, ranging from immunization records to surgical history. However, the benefits of carrying a copy of personal health information are becoming increasingly evident. This project aims to create a simple, secure, and cohesive application that stores and retrieves user health information backed by Google’s Firebase cloud infrastructure. Data was collected to both explore the current need for such an application, and to test the usability of the product. The former was done using a multiple-choice survey distributed through social media to understand the necessity for a patient-held health file (PHF). Subsequently, user testing was performed with the intent to track the success of our application in meeting those needs. According to the data, there was a trend that suggested a significant need for a healthcare information storage device. This application, allowing for efficient and simple medical information storage and retrieval, was created for a target audience of those seeking to improve their medical information awareness, with a primary focus on the elderly population. Specific correlations between the frequency of physician visits and app usage were identified to target the potential use cases of our app. The outcome of this project succeeded in meeting the significant need for increased patient medical awareness in the healthcare community.
ContributorsUpponi, Rohan Sachin (Co-author) / Somayaji, Vasishta (Co-author) / McDaniel, Troy (Thesis director) / Meuth, Ryan (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
131390-Thumbnail Image.png
Description
For our creative project, we initially wanted to work on a web application that would allow people with busy schedules to easily create and share events while also discovering other events that may interest them. With that in mind, we created the Group Event Planner App, a full stack project

For our creative project, we initially wanted to work on a web application that would allow people with busy schedules to easily create and share events while also discovering other events that may interest them. With that in mind, we created the Group Event Planner App, a full stack project that lays down a foundation for all of our goals while focusing primarily on the proposed recommendation algorithms that enable its users to discover events that are likely to pique their interest. The development of our recommendation algorithms took inspiration from existing implementations, such as those at Amazon, YouTube, and Netflix, and resulted in a creative amalgamation.
ContributorsRussell, Preston (Co-author) / Sonnier, Connor (Co-author) / Chen, Yinong (Thesis director) / Meuth, Ryan (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
130975-Thumbnail Image.png
Description
Immunotherapy is an effective treatment for cancer which enables the patient's immune system to recognize tumor cells as pathogens. In order to design an individualized treatment, the t cell receptors (TCR) which bind to a tumor's unique antigens need to be determined. We created a convolutional neural network to predict

Immunotherapy is an effective treatment for cancer which enables the patient's immune system to recognize tumor cells as pathogens. In order to design an individualized treatment, the t cell receptors (TCR) which bind to a tumor's unique antigens need to be determined. We created a convolutional neural network to predict the binding affinity between a given TCR and antigen to enable this.
ContributorsCai, Michael Ray (Author) / Lee, Heewook (Thesis director) / Meuth, Ryan (Committee member) / Computer Science and Engineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2020-12
131529-Thumbnail Image.png
Description
RecyclePlus is an iOS mobile application that allows users to be knowledgeable in the realms of sustainability. It gives encourages users to be environmental responsible by providing them access to recycling information. In particular, it allows users to search up certain materials and learn about its recyclability and how to

RecyclePlus is an iOS mobile application that allows users to be knowledgeable in the realms of sustainability. It gives encourages users to be environmental responsible by providing them access to recycling information. In particular, it allows users to search up certain materials and learn about its recyclability and how to properly dispose of the material. Some searches will show locations of facilities near users that collect certain materials and dispose of the materials properly. This is a full stack software project that explores open source software and APIs, UI/UX design, and iOS development.
ContributorsTran, Nikki (Author) / Ganesh, Tirupalavanam (Thesis director) / Meuth, Ryan (Committee member) / Watts College of Public Service & Community Solut (Contributor) / Department of Information Systems (Contributor) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
132553-Thumbnail Image.png
Description
Debate provides a valuable educational opportunity for students to learn a variety of portable research and public speaking skills, but many of its goals are hindered by the lack of a dedicated software. Currently, the primary tool for research and presentation of evidence is paperlessdebate.com's Verbatim, which is built as

Debate provides a valuable educational opportunity for students to learn a variety of portable research and public speaking skills, but many of its goals are hindered by the lack of a dedicated software. Currently, the primary tool for research and presentation of evidence is paperlessdebate.com's Verbatim, which is built as a template for Microsoft Word. While functional, Verbatim suffers from several shortcomings; its reliance on Word means that it cannot be fully cross-platform, and it also means that it is difficult to streamline Verbatim's workflow for the particular needs of debaters. Thus, the goal of this project was to fill the need for a stand-alone, cross platform application that debaters (and coaches) can use to research and present evidence. The bulk of the project consisted of creating a specialized editor, including a variety of features catered towards usability in a range of debate contexts. Additionally, the software is integrated with a back end database such that it can also replace the mixture of storage solutions (such as Dropbox and Microsoft's OneDrive) that teams currently use to maintain and share their data. In order to make the software more extensible and to improve its accessibility, it is released as free open source software under the GNU General Public License v3.0. This paper describes the core features of the application and the motivation behind those features' implementations, and briefly includes a discussion of the companion mobile app for Android devices. It also reviews the technologies that were used to create the software's implementation.
ContributorsRedman, Colin (Author) / Symonds, Adam (Thesis director) / Meuth, Ryan (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
133901-Thumbnail Image.png
Description
This thesis dives into the world of artificial intelligence by exploring the functionality of a single layer artificial neural network through a simple housing price classification example while simultaneously considering its impact from a data management perspective on both the software and hardware level. To begin this study, the universally

This thesis dives into the world of artificial intelligence by exploring the functionality of a single layer artificial neural network through a simple housing price classification example while simultaneously considering its impact from a data management perspective on both the software and hardware level. To begin this study, the universally accepted model of an artificial neuron is broken down into its key components and then analyzed for functionality by relating back to its biological counterpart. The role of a neuron is then described in the context of a neural network, with equal emphasis placed on how it individually undergoes training and then for an entire network. Using the technique of supervised learning, the neural network is trained with three main factors for housing price classification, including its total number of rooms, bathrooms, and square footage. Once trained with most of the generated data set, it is tested for accuracy by introducing the remainder of the data-set and observing how closely its computed output for each set of inputs compares to the target value. From a programming perspective, the artificial neuron is implemented in C so that it would be more closely tied to the operating system and therefore make the collected profiler data more precise during the program's execution. The program is designed to break down each stage of the neuron's training process into distinct functions. In addition to utilizing more functional code, the struct data type is used as the underlying data structure for this project to not only represent the neuron but for implementing the neuron's training and test data. Once fully trained, the neuron's test results are then graphed to visually depict how well the neuron learned from its sample training set. Finally, the profiler data is analyzed to describe how the program operated from a data management perspective on the software and hardware level.
ContributorsRichards, Nicholas Giovanni (Author) / Miller, Phillip (Thesis director) / Meuth, Ryan (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
This research ventures to adjust the Algebra 2 Core Standards set by the Arizona Department of Education so that computer science concepts may be taught in parallel with the mathematical concepts in Algebra 2 in order to facilitate a better understanding of both subjects. The close relation to computer science

This research ventures to adjust the Algebra 2 Core Standards set by the Arizona Department of Education so that computer science concepts may be taught in parallel with the mathematical concepts in Algebra 2 in order to facilitate a better understanding of both subjects. The close relation to computer science and mathematics make this course possible. Students will be more prepared for university level education when they understand how technology works rather than simply how to use it. The solution is to create an online set of modules that can be taught alongside the high school mathematics course, Algebra 2. The solution contains a set of five modules that parallel with the Arizona core standards of the class. There are several obstacles that needed to be overcome in order to create online modules that would fit the needs of schools, students and teachers. This solution will reach students quickly as the hope is that it will become a requirement according to the Arizona Department of Education core standards. The course will be easily accessible to students as it is online and the course will fit into the existing education system, which would not require state laws to be passed in order to require the teaching of computer science. The goal is to bridge the gap between secondary education and college level S.T.E.M. education specifically in reference to computer science so that students start college with a strong understanding of how technology works in order to help them become more successful in the future.
ContributorsHickie, Kendall Shea (Author) / Miller, Phillip (Thesis director) / Meuth, Ryan (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
135078-Thumbnail Image.png
Description
The Internet of Things has spread Wi-Fi connectivity to household and business devices everywhere. It is important that we understand IoT's risks and capabilities as its popularity continues to grow, and that we recognize new and exciting uses for it. In this project, the ESP8266 Wi-Fi controller, powered by a

The Internet of Things has spread Wi-Fi connectivity to household and business devices everywhere. It is important that we understand IoT's risks and capabilities as its popularity continues to grow, and that we recognize new and exciting uses for it. In this project, the ESP8266 Wi-Fi controller, powered by a lithium battery, is used to transmit messages from a user's browser or mobile phone to an OLED display. The ESP8266 is a system on a chip (SOC) which boasts impressive features such as full TCP/IP stack, 1 MB of flash memory, and a 32-bit CPU. A web server is started on the ESP8266 which listens at a specific port and relays any strings from the client back to the display, acting as a simple notification system for a busy individual such as a professor. The difficulties with this project stemmed from the security protocol of Arizona State University's Wi-Fi network and from the limitations of the Wi-Fi chip itself. Several solutions are suggested, such as utilizing a personal cellular broadband router and polling a database for stored strings through a service such as Data.Sparkfun.com.
ContributorsKovatcheva, Simona Kamenova (Author) / Burger, Kevin (Thesis director) / Meuth, Ryan (Committee member) / Computer Science and Engineering Program (Contributor) / School of International Letters and Cultures (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12